Instrument selection for estimation of a forward-looking Phillips Curve

We show that data-driven instrument selection based on the LASSOestimator can perform well comparative to the usual ad hoc instrument set for single equation estimation of a forward-looking Phillips Curve, when the overall identification condition is strong or in cases when the instruments are not very weak. We conclude that in face of model uncertainty and/or some potentially weak instruments within a large number of candidates, data-driven selection may provide a disciplined and more reliable estimation strategy.